{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OEllFa_0d94M",
        "outputId": "61744dcf-a93d-47a5-dfee-f01e09b09eea"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import LSTM, Dense, Dropout, BatchNormalization\n",
        "from tensorflow.keras.callbacks import EarlyStopping\n",
        "from tensorflow.keras.optimizers import SGD\n",
        "from tensorflow.keras.optimizers.schedules import ExponentialDecay\n",
        "import tensorflow as tf\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tf.random.set_seed(42)\n",
        "np.random.seed(42)\n",
        "\n",
        "df = pd.read_csv('/content/drive/MyDrive/ML projects/dataset/ppg_data.csv')\n",
        "\n",
        "scaler = MinMaxScaler()\n",
        "data_scaled = scaler.fit_transform(df)\n",
        "\n",
        "def create_sequences(data, seq_length):\n",
        "    X, y = [], []\n",
        "    for i in range(len(data) - seq_length):\n",
        "        X.append(data[i:i+seq_length])\n",
        "        y.append(data[i+seq_length])\n",
        "    return np.array(X), np.array(y)\n",
        "\n",
        "seq_length = 10\n",
        "X, y = create_sequences(data_scaled, seq_length)\n",
        "X = X.reshape((X.shape[0], X.shape[1], 2))\n",
        "\n",
        "train_size = int(len(X) * 0.7)\n",
        "X_train, X_test = X[:train_size], X[train_size:]\n",
        "y_train, y_test = y[:train_size], y[train_size:]\n",
        "\n",
        "lr_schedule = ExponentialDecay(\n",
        "    initial_learning_rate=0.0005,\n",
        "    decay_steps=10000,\n",
        "    decay_rate=0.9\n",
        ")\n",
        "optimizer = SGD(learning_rate=lr_schedule, momentum=0.9)\n",
        "\n",
        "model = Sequential([\n",
        "    LSTM(25, return_sequences=True, input_shape=(seq_length, 2)),\n",
        "    BatchNormalization(),\n",
        "    Dropout(0.15),\n",
        "    LSTM(25, return_sequences=False),\n",
        "    BatchNormalization(),\n",
        "    Dropout(0.1),\n",
        "    Dense(2)\n",
        "])\n",
        "\n",
        "model.compile(optimizer=optimizer, loss='mse')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8OmdV9s7pLGF",
        "outputId": "d1a1ecb1-d18a-43cf-c323-1e7e629230d6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.11/dist-packages/keras/src/layers/rnn/rnn.py:200: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
            "  super().__init__(**kwargs)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 385
        },
        "id": "PjEYeE2Hr8Fh",
        "outputId": "687ef85b-1bfb-4879-fffc-b242fda5625c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1mModel: \"sequential_4\"\u001b[0m\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_4\"</span>\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
              "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                        \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape               \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m        Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
              "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
              "│ lstm_8 (\u001b[38;5;33mLSTM\u001b[0m)                        │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m10\u001b[0m, \u001b[38;5;34m25\u001b[0m)              │           \u001b[38;5;34m2,800\u001b[0m │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ batch_normalization_8                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m10\u001b[0m, \u001b[38;5;34m25\u001b[0m)              │             \u001b[38;5;34m100\u001b[0m │\n",
              "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)                 │                             │                 │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ dropout_8 (\u001b[38;5;33mDropout\u001b[0m)                  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m10\u001b[0m, \u001b[38;5;34m25\u001b[0m)              │               \u001b[38;5;34m0\u001b[0m │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ lstm_9 (\u001b[38;5;33mLSTM\u001b[0m)                        │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m25\u001b[0m)                  │           \u001b[38;5;34m5,100\u001b[0m │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ batch_normalization_9                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m25\u001b[0m)                  │             \u001b[38;5;34m100\u001b[0m │\n",
              "│ (\u001b[38;5;33mBatchNormalization\u001b[0m)                 │                             │                 │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ dropout_9 (\u001b[38;5;33mDropout\u001b[0m)                  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m25\u001b[0m)                  │               \u001b[38;5;34m0\u001b[0m │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ dense_4 (\u001b[38;5;33mDense\u001b[0m)                      │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m2\u001b[0m)                   │              \u001b[38;5;34m52\u001b[0m │\n",
              "└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓\n",
              "┃<span style=\"font-weight: bold\"> Layer (type)                         </span>┃<span style=\"font-weight: bold\"> Output Shape                </span>┃<span style=\"font-weight: bold\">         Param # </span>┃\n",
              "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩\n",
              "│ lstm_8 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>)                        │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">10</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">25</span>)              │           <span style=\"color: #00af00; text-decoration-color: #00af00\">2,800</span> │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ batch_normalization_8                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">10</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">25</span>)              │             <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span> │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)                 │                             │                 │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ dropout_8 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)                  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">10</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">25</span>)              │               <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ lstm_9 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">LSTM</span>)                        │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">25</span>)                  │           <span style=\"color: #00af00; text-decoration-color: #00af00\">5,100</span> │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ batch_normalization_9                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">25</span>)                  │             <span style=\"color: #00af00; text-decoration-color: #00af00\">100</span> │\n",
              "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>)                 │                             │                 │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ dropout_9 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)                  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">25</span>)                  │               <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
              "├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤\n",
              "│ dense_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                      │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">2</span>)                   │              <span style=\"color: #00af00; text-decoration-color: #00af00\">52</span> │\n",
              "└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m8,152\u001b[0m (31.84 KB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">8,152</span> (31.84 KB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m8,052\u001b[0m (31.45 KB)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">8,052</span> (31.45 KB)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m100\u001b[0m (400.00 B)\n"
            ],
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">100</span> (400.00 B)\n",
              "</pre>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "early_stopping = EarlyStopping(monitor='val_loss', patience=5, restore_best_weights=True)\n",
        "history=model.fit(X_train, y_train, epochs=3, batch_size=32, validation_data=(X_test, y_test), callbacks=[early_stopping], verbose=1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bW2vx_2upRkP",
        "outputId": "ca448831-1c70-48f8-a788-79ffd2a78c65"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/3\n",
            "\u001b[1m7875/7875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m121s\u001b[0m 15ms/step - loss: 0.0602 - val_loss: 0.0202\n",
            "Epoch 2/3\n",
            "\u001b[1m7875/7875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m138s\u001b[0m 14ms/step - loss: 0.0016 - val_loss: 0.0024\n",
            "Epoch 3/3\n",
            "\u001b[1m7875/7875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m140s\u001b[0m 14ms/step - loss: 8.6071e-04 - val_loss: 0.0047\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tf.keras.callbacks.History()\n",
        "history = model.history\n",
        "plt.plot(history.history['loss'], label='Training Loss')\n",
        "plt.plot(history.history['val_loss'], label='Validation Loss')\n",
        "plt.title('Training and Validation Loss')\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Loss')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "ElttM2M9rhqx",
        "outputId": "4009a7a9-4ab4-40c4-d0ac-f2070a7643a6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "future_steps = 20\n",
        "input_sequence = X_test[-1].reshape(1, seq_length, 2)\n",
        "generated_signal = []\n",
        "\n",
        "for _ in range(future_steps):\n",
        "    prediction = model.predict(input_sequence)\n",
        "    generated_signal.append(prediction[0])\n",
        "    input_sequence = np.roll(input_sequence, -1, axis=1)\n",
        "    input_sequence[0, -1, :] = prediction\n",
        "\n",
        "generated_signal = scaler.inverse_transform(generated_signal)\n",
        "\n",
        "plt.figure(figsize=(12, 6))\n",
        "plt.plot(range(future_steps), generated_signal[:, 0], label=\"Generated Signal\", color='blue')\n",
        "plt.legend()\n",
        "plt.title(\"Generated Signal\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 892
        },
        "id": "jZW2TF4epktt",
        "outputId": "892b2f48-bf2b-4d26-b0a8-1e1e3608fdc4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 403ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 47ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 45ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 41ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 42ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 46ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 49ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 39ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 44ms/step\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 40ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.save(\"test.h5\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RARHcK-oI7Im",
        "outputId": "14bc3f9d-ab02-4e42-a86d-45bab04164c0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:absl:You are saving your model as an HDF5 file via `model.save()` or `keras.saving.save_model(model)`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')` or `keras.saving.save_model(model, 'my_model.keras')`. \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from tensorflow.keras.models import load_model\n",
        "from tensorflow.keras.losses import MeanSquaredError\n",
        "import io\n",
        "\n",
        "# Load the model with custom_objects\n",
        "model = load_model('test.h5', custom_objects={'mse': MeanSquaredError()})\n",
        "\n",
        "# Load your data\n",
        "data = \"\"\"Infra-Red PPG,Red PPG\n",
        "231.3,195.6\n",
        "237.0,202.7\n",
        "240.4,208.8\n",
        "243.9,220.6\n",
        "248.4,239.2\n",
        "251.6,257.0\n",
        "249.3,262.0\n",
        "239.7,246.7\n",
        "226.4,215.4\n",
        "217.5,183.0\n",
        "220.4,166.1\n",
        "236.8,173.0\n",
        "260.6,198.4\n",
        "281.4,228.8\n",
        "290.8,250.4\n",
        "286.4,257.1\n",
        "272.2,250.3\n",
        "254.7,235.1\n",
        "238.9,216.8\n",
        "225.6,199.0\n",
        "212.6,184.7\n",
        "197.3,176.1\n",
        "178.7,173.4\n",
        "158.6,173.6\n",
        "139.9,171.6\n",
        "124.9,163.9\n",
        "113.7,151.0\n",
        "104.4,137.0\n",
        "94.8,125.9\n",
        "84.0,119.1\n",
        "73.5,114.8\n",
        "65.5,111.2\n",
        "61.1,108.2\n",
        "58.9,107.3\n",
        "55.2,108.8\n",
        "46.9,110.2\n",
        "33.7,108.0\n",
        "18.5,100.7\n",
        "5.5,91.2\n",
        "-2.6,84.7\n",
        "-6.6,84.4\n",
        "-10.5,88.1\n",
        "-18.9,89.0\n",
        "-34.3,80.5\n",
        "-54.9,61.0\n",
        "-75.7,35.3\n",
        "-91.0,11.4\n",
        "-98.3,-4.6\n",
        "-99.9,-11.6\n",
        "-101.7,-13.9\n",
        "-109.3,-18.0\n",
        "-124.6,-29.3\n",
        "-144.7,-49.4\n",
        "-164.8,-76.6\n",
        "-182.1,-106.4\n",
        "-197.4,-133.8\n",
        "-213.6,-154.8\n",
        "-231.7,-167.2\n",
        "-248.9,-171.5\n",
        "-260.4,-170.0\n",
        "-263.4,-166.6\n",
        "-260.5,-164.8\n",
        "-258.8,-167.6\n",
        "-264.6,-176.2\n",
        "-279.6,-190.4\n",
        "-299.7,-207.8\n",
        "-318.3,-225.2\n",
        "-331.0,-238.8\n",
        "-338.2,-245.8\n",
        "-343.6,-245.7\n",
        "-350.0,-240.0\n",
        "-357.4,-231.2\n",
        "-362.8,-221.8\n",
        "-363.5,-211.9\n",
        "-358.8,-200.2\n",
        "-351.3,-184.6\n",
        "-345.1,-165.7\n",
        "-343.7,-147.9\n",
        "-349.0,-138.8\n",
        "-361.4,-145.3\n",
        "-380.0,-169.4\n",
        "-403.1,-206.0\n",
        "-428.0,-244.6\n",
        "-452.0,-274.6\n",
        "-473.1,-291.4\n",
        "-490.9,-297.7\n",
        "-505.8,-301.3\n",
        "-518.0,-308.8\n",
        "-527.5,-320.9\n",
        "-534.3,-332.5\n",
        "-539.9,-337.2\n",
        "-546.8,-332.0\n",
        "-554.7,-319.1\n",
        "-558.3,-303.4\n",
        "-545.9,-287.7\n",
        "-504.1,-269.8\n",
        "-425.6,-243.9\n",
        "-314.4,-205.6\n",
        "-186.0,-156.3\n",
        "-61.1,-103.3\n",
        "42.8,-56.4\n",
        "117.8,-22.3\n",
        "165.0,-1.7\n",
        "190.5,9.4\n",
        "200.5,16.5\n",
        "198.6,22.4\n",
        "186.7,26.9\n",
        "167.0,28.7\n",
        "143.4,27.8\n",
        "122.0,26.5\n",
        "108.5,27.4\n",
        "106.4,31.6\n",
        "115.5,37.4\n",
        "131.9,41.7\n",
        "150.4,42.7\n",
        "166.8,41.5\n",
        "180.4,41.1\n",
        "193.3,44.6\n",
        "208.5,52.4\n",
        "227.0,62.4\n",
        "246.8,71.2\n",
        "263.9,76.4\n",
        "273.8,77.5\n",
        "273.8,75.9\n",
        "263.3,73.0\n",
        "243.9,69.6\n",
        "219.4,66.3\n",
        "195.0,63.5\n",
        "175.8,61.9\n",
        "165.5,61.8\n",
        "164.2,62.4\n",
        "169.2,62.8\n",
        "177.4,62.5\n",
        "187.4,62.5\n",
        "200.4,64.4\n",
        "217.5,69.8\n",
        "237.7,78.3\n",
        "257.0,88.3\n",
        "270.2,97.2\n",
        "274.4,103.7\n",
        "270.9,107.9\n",
        "263.4,111.0\n",
        "256.2,114.1\n",
        "251.5,117.8\n",
        "249.2,122.0\n",
        "248.1,126.8\n",
        "247.4,132.3\n",
        "246.7,138.5\n",
        "246.0,144.8\n",
        "245.2,149.7\n",
        "244.0,151.4\n",
        "241.5,149.5\n",
        "237.2,144.9\n",
        "231.0,139.8\"\"\"\n",
        "\n",
        "df = pd.read_csv(io.StringIO(data))\n",
        "\n",
        "missing_indices = [20,40, 50, 80,100, 120]\n",
        "for index in missing_indices:\n",
        "    df.loc[index, ['Infra-Red PPG', 'Red PPG']] = 0\n",
        "\n",
        "scaler = MinMaxScaler()\n",
        "data_scaled = scaler.fit_transform(df.values)\n",
        "\n",
        "def create_sequences(data, seq_length):\n",
        "    X, y = [], []\n",
        "    for i in range(len(data) - seq_length):\n",
        "        X.append(data[i:i + seq_length])\n",
        "        y.append(data[i + seq_length])\n",
        "    return np.array(X), np.array(y)\n",
        "\n",
        "seq_length = 10\n",
        "X, y = create_sequences(data_scaled, seq_length)\n",
        "X = X.reshape((X.shape[0], X.shape[1], 2))\n",
        "\n",
        "y_pred = model.predict(X)\n",
        "y_pred = scaler.inverse_transform(y_pred)\n",
        "y = scaler.inverse_transform(y)\n",
        "\n",
        "def detect_missing_pulses(true_values, predicted_values):\n",
        "    differences = np.abs(true_values - predicted_values)\n",
        "    anomalies = np.mean(differences, axis=1) > 100\n",
        "    return np.where(anomalies)[0]\n",
        "\n",
        "missing_pulse_indices = detect_missing_pulses(y, y_pred)\n",
        "print(\"Missing Pulse Detected at Indices:\", missing_pulse_indices)\n",
        "\n",
        "plt.figure(figsize=(12, 6))\n",
        "plt.plot(y[:, 0], label=\"True Infra-Red PPG\", linestyle='dotted')\n",
        "plt.plot(y_pred[:, 0], label=\"Predicted Infra-Red PPG\", linestyle='dashed')\n",
        "\n",
        "for index in missing_indices:\n",
        "    if index >= seq_length:\n",
        "        plt.scatter(index, df['Infra-Red PPG'].values[index], color='green', marker='o', label='Added Missing Pulse' if index == missing_indices[0] else \"\")\n",
        "\n",
        "plt.scatter(missing_pulse_indices + seq_length, y[missing_pulse_indices, 0], color='red', label=\"Detected Missing Pulses\", marker='x')\n",
        "\n",
        "plt.legend()\n",
        "plt.title(\"Infra-Red PPG Prediction and Missing Pulse Detection (Zeros)\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 669
        },
        "id": "JsLp-vuoMeQt",
        "outputId": "dfa6e3b4-a9a2-4a2e-d83c-e7b906ed7a86"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:absl:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m5/5\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 91ms/step\n",
            "Missing Pulse Detected at Indices: [  6   7   8   9  10  42  43  44  45  46  47  48  49  50  51  52  53  54\n",
            "  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71  72\n",
            "  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  90\n",
            "  91 110]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n",
        "\n",
        "# Predict the test data\n",
        "y_pred = model.predict(X_test)\n",
        "y_pred_rescaled = scaler.inverse_transform(y_pred)\n",
        "y_test_rescaled = scaler.inverse_transform(y_test)\n",
        "\n",
        "# Calculate metrics\n",
        "mse = mean_squared_error(y_test_rescaled, y_pred_rescaled)\n",
        "mae = mean_absolute_error(y_test_rescaled, y_pred_rescaled)\n",
        "r2 = r2_score(y_test_rescaled, y_pred_rescaled)\n",
        "\n",
        "print(f\"Mean Squared Error (MSE): {mse}\")\n",
        "print(f\"Mean Absolute Error (MAE): {mae}\")\n",
        "print(f\"R² Score: {r2}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6CvAULodPNIL",
        "outputId": "4f6960b8-49c5-43d4-db29-e68853645880"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m3375/3375\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m14s\u001b[0m 4ms/step\n",
            "Mean Squared Error (MSE): 1168.3141629009108\n",
            "Mean Absolute Error (MAE): 28.041382953995722\n",
            "R² Score: -49.65613509466572\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12, 6))\n",
        "plt.plot(y_test_rescaled[:, 0], label=\"True Infra-Red PPG\", linestyle='solid')\n",
        "plt.plot(y_pred_rescaled[:, 0], label=\"Predicted Infra-Red PPG\", linestyle='dashed')\n",
        "plt.legend()\n",
        "plt.title(\"Infra-Red PPG: True vs Predicted\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "id": "6VXMpQQlM5Za",
        "outputId": "bcbadb95-2c36-4c25-f43f-ab17763b9d46"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}